ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS

Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long‐term population growth or decay. Many decisions for threatened and en...

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Published in:Ecological Applications
Main Authors: Deines, A., Peterson, E., Boeckner, D., Boyle, J., Keighley, A., Kogut, J., Lubben, J., Rebarber, R., Ryan, R., Tenhumberg, B., Townley, S., Tyre, A. J.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2007
Subjects:
Online Access:http://dx.doi.org/10.1890/06-1090.1
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spelling crwiley:10.1890/06-1090.1 2024-03-31T07:54:53+00:00 ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS Deines, A. Peterson, E. Boeckner, D. Boyle, J. Keighley, A. Kogut, J. Lubben, J. Rebarber, R. Ryan, R. Tenhumberg, B. Townley, S. Tyre, A. J. 2007 http://dx.doi.org/10.1890/06-1090.1 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1890%2F06-1090.1 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1890/06-1090.1 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Ecological Applications volume 17, issue 8, page 2175-2183 ISSN 1051-0761 1939-5582 Ecology journal-article 2007 crwiley https://doi.org/10.1890/06-1090.1 2024-03-04T13:01:45Z Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long‐term population growth or decay. Many decisions for threatened and endangered species are made with poor or no information. We can still make decisions under these circumstances in a manner that is highly defensible, even without making assumptions about the distribution of uncertainty, or limiting ourselves to discussions of single, infinitesimally small changes in the parameters. Suppose that the model (determined by the data) for the population in question predicts long‐term growth. Our goal is to determine how uncertain the data can be before the model loses this property. Some uncertainties will maintain long‐term growth, and some will lead to long‐term decay. The uncertainties are typically structured, and can be described by several parameters. We show how to determine which parameters maintain long‐term growth. We illustrate the advantages of the method by applying it to a Peregrine Falcon population. The U.S. Fish and Wildlife Service recently decided to allow minimal harvesting of Peregrine Falcons after their recent removal from the Endangered Species List. Based on published demographic rates, we find that an asymptotic growth rate λ > 1 is guaranteed with 5% harvest rate up to 3% error in adult survival if no two‐year‐olds breed, and up to 11% error if all two‐year‐olds breed. If a population growth rate of 3% or greater is desired, the acceptable error in adult survival decreases to between 1% and 6% depending of the proportion of two‐year‐olds that breed. These results clearly show the interactions between uncertainties in different parameters, and suggest that a harvest decision at this stage may be premature without solid data on adult survival and the frequency of breeding by young adults. Article in Journal/Newspaper peregrine falcon Wiley Online Library Ecological Applications 17 8 2175 2183
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
topic Ecology
spellingShingle Ecology
Deines, A.
Peterson, E.
Boeckner, D.
Boyle, J.
Keighley, A.
Kogut, J.
Lubben, J.
Rebarber, R.
Ryan, R.
Tenhumberg, B.
Townley, S.
Tyre, A. J.
ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
topic_facet Ecology
description Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long‐term population growth or decay. Many decisions for threatened and endangered species are made with poor or no information. We can still make decisions under these circumstances in a manner that is highly defensible, even without making assumptions about the distribution of uncertainty, or limiting ourselves to discussions of single, infinitesimally small changes in the parameters. Suppose that the model (determined by the data) for the population in question predicts long‐term growth. Our goal is to determine how uncertain the data can be before the model loses this property. Some uncertainties will maintain long‐term growth, and some will lead to long‐term decay. The uncertainties are typically structured, and can be described by several parameters. We show how to determine which parameters maintain long‐term growth. We illustrate the advantages of the method by applying it to a Peregrine Falcon population. The U.S. Fish and Wildlife Service recently decided to allow minimal harvesting of Peregrine Falcons after their recent removal from the Endangered Species List. Based on published demographic rates, we find that an asymptotic growth rate λ > 1 is guaranteed with 5% harvest rate up to 3% error in adult survival if no two‐year‐olds breed, and up to 11% error if all two‐year‐olds breed. If a population growth rate of 3% or greater is desired, the acceptable error in adult survival decreases to between 1% and 6% depending of the proportion of two‐year‐olds that breed. These results clearly show the interactions between uncertainties in different parameters, and suggest that a harvest decision at this stage may be premature without solid data on adult survival and the frequency of breeding by young adults.
format Article in Journal/Newspaper
author Deines, A.
Peterson, E.
Boeckner, D.
Boyle, J.
Keighley, A.
Kogut, J.
Lubben, J.
Rebarber, R.
Ryan, R.
Tenhumberg, B.
Townley, S.
Tyre, A. J.
author_facet Deines, A.
Peterson, E.
Boeckner, D.
Boyle, J.
Keighley, A.
Kogut, J.
Lubben, J.
Rebarber, R.
Ryan, R.
Tenhumberg, B.
Townley, S.
Tyre, A. J.
author_sort Deines, A.
title ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_short ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_full ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_fullStr ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_full_unstemmed ROBUST POPULATION MANAGEMENT UNDER UNCERTAINTY FOR STRUCTURED POPULATION MODELS
title_sort robust population management under uncertainty for structured population models
publisher Wiley
publishDate 2007
url http://dx.doi.org/10.1890/06-1090.1
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1890%2F06-1090.1
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1890/06-1090.1
genre peregrine falcon
genre_facet peregrine falcon
op_source Ecological Applications
volume 17, issue 8, page 2175-2183
ISSN 1051-0761 1939-5582
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1890/06-1090.1
container_title Ecological Applications
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